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To understand statistics properly from a comprehensive point of view, each statistics student needs to know about the diverse fields of statistics. Time and again, the type of job one is involved in hides the other facets of statistics, but to fully welcome its value and splendor, it is imperative to comprehend the overarching theme behind statistical analysis. You will learn about the two broad branches of statistics in this article.

Descriptive Statistics as one of the branches of Statistics

This is a subfield of statistics that are involved with the presentation and collection of information. Being the foremost part of statistical analysis, it involves complex needs that the statistician should be aware of. It is concerned with designing experiments, identifying and selecting the correct focus crowd for study.

It's vital to identify the type of focus group as you do not intend to choose a bias group that will creep into your experiment. Descriptive statistics presents itself in various forms such as finding averages, tables, graphs and diagrams, and so forth. The measures are useful in the estimation of data. These measures fall into several types.

  • Measures of central tendency; which locates the distance by various parts. It includes the mean, median and mode.
  • Measures of variability; this involves aspects such as variance, standard deviation, minimum and maximum variables, and lastly the skewness and kurtosis.
  • Measure of frequency; shows how often something occur.
  • Measure of dispersion; identifies the spread of scores by giving the intervals.
  • Measure of position; this describes how scores fall in relation to one another.
  • In a nutshell, descriptive statistics help in describing and comprehending features of a specific data set by giving short summaries about the sample and measures of the data.

    Inferential Statistics

    This subfield necessitates depicting the right conclusion from the statistical analysis that has been conducted using descriptive analysis. This is to say; it is the inferences that make studies imperative with the help of techniques useful for data analysis.

    It is mostly concerned with predictions of the future and generalizations about a population through study. The study in this context involves a small sample population that helps to determine how the general population behaves. One vital significance of inferential statistics is that the result is likely to be relevant based on the design of the experiment.

    An excellent design reassures the researcher of a probable good conclusion of the study. Inferential statistics make a population proposal, using population-drawn data with some form of sampling. There are three type of inferential statistics.

  • T-tests which can be used to compare means. It falls under three models namely, one sample, independent sample and dependent/paired sample t-tests respectively.
  • Regression is a procedure that enables you to predict a result variable based on some predictor variable's knowledge.
  • ANOVA, pretty much similar to t-test but it compares various means at the same time. It also falls into three models namely, one way, repeated measures, and factorial ANOVA.
  • Ultimately, descriptive and inferential statistics go hand in hand, and one cannot serve its purpose without the other. An excellent scientific methodology must be followed in both of these levels of statistical analysis, and mutually, these branches of statistics are equally important to a researcher. You can seek for statistics assignment help today by contacting us, Get in touch with us for high quality work and further assistance in the subject.

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